An Empirical Study on the Factors Influencing Residents' Income in Pujiang County, Jinhua City

The purpose of this paper is to explore the relationship between residents' income and investment in the three major industries and fixed assets in Pujiang County, Jinhua City. Based on the time series data of the three major industries and fixed asset investment in Pujiang County, Jinhua City from 1999 to 2019, this study employed methods such as ADF test, cointegration analysis, stepwise regression to eliminate multicollinearity, and LM test to examine the relationship between residents' income and the three major industries as well as fixed asset investment in Pujiang County, Jinhua City. The research findings indicate that the total output of the primary and secondary industries has no significant impact on the local residents' income. However, the tertiary industry and fixed asset investment have a significant impact on the local residents' income. Moreover, for every 1% increase in the GDP of the tertiary industry, the total wage income of the residents increases by an average of 0.70%. Similarly, for every 1% increase in fixed investment, the total wage income of the residents increases by an average of 0.12%. Additionally, the autoregressive coefficients AR(9) and AR(10) are also significant, suggesting that the growth of local residents' income is a long-term process. Based on these analyses, the following policy recommendations are proposed.

Authors

Publication Details

Journal
Journal of Science Technology and Society
Published
2025-01-09
DOI
https://doi.org/10.57237/j.jsts.2024.02.003
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Empirical Study on the Factors Influencing Residents' Income in Pujiang County, Jinhua City

Fangjun Liu, Ou Chuanbiao
Journal of Science Technology and Society
Energy, Environment, Economic Growth
article

An Empirical Study on the Factors Influencing Residents' Income in Pujiang County, Jinhua City

Fangjun Liu, Ou Chuanbiao
article en

Abstract

The purpose of this paper is to explore the relationship between residents' income and investment in the three major industries and fixed assets in Pujiang County, Jinhua City. Based on the time series data of the three major industries and fixed asset investment in Pujiang County, Jinhua City from 1999 to 2019, this study employed methods such as ADF test, cointegration analysis, stepwise regression to eliminate multicollinearity, and LM test to examine the relationship between residents' income and the three major industries as well as fixed asset investment in Pujiang County, Jinhua City. The research findings indicate that the total output of the primary and secondary industries has no significant impact on the local residents' income. However, the tertiary industry and fixed asset investment have a significant impact on the local residents' income. Moreover, for every 1% increase in the GDP of the tertiary industry, the total wage income of the residents increases by an average of 0.70%. Similarly, for every 1% increase in fixed investment, the total wage income of the residents increases by an average of 0.12%. Additionally, the autoregressive coefficients AR(9) and AR(10) are also significant, suggesting that the growth of local residents' income is a long-term process. Based on these analyses, the following policy recommendations are proposed.

Journal of Science Technology and Society
No poverty
Openalex Percentile: Top 99%
Energy, Environment, Economic Growth
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.